Andrej Baranovskij Blog
Blog about Oracle, Full Stack, Machine Learning and Cloud
Monday, April 12, 2021
What I Hate About Machine Learning
I describe what I hate most about Machine Learning. Hopefully, this video will not scare you, but on the opposite, it will inspire you to start with Machine Learning.
Labels:
Machine Learning
Sunday, April 4, 2021
What I Love About Machine Learning
I describe what I love most about Machine Learning. Hopefully, this will inspire you to jump into the exciting field of ML.
Labels:
Machine Learning
Sunday, March 28, 2021
My Machine Learning Experience
I talk about my own Machine Learning experience and why I decided to convert to ML from enterprise software development with Oracle tools.
Labels:
Machine Learning
Sunday, March 14, 2021
FastAPI and Oracle DB Client in Docker
I describe how to dockerize Oracle DB Client with FastAPI and Uvicorn. The end result - you will be able to connect to Oracle Cloud DB and expose REST services through FastAPI in Python.
Labels:
Database,
Docker,
FastAPI,
Oracle Cloud,
Python
Sunday, March 7, 2021
TensorFlow.js Blueprint App Step by Step
I describe how to prepare data that comes from API into TensorFlow.js Dataset structure, how to shuffle, normalize, one-hot-encode, and batch the data. Next, I go on model training and explain why fitDataset is recommended way to train a neural network in TensorFlow.js. At last, I show how to do inference and print the results. This app is built with React, but the same code can be reused with any JS toolkit/framework.
Labels:
JavaScript,
Machine Learning,
React,
TensorFlow
Saturday, February 27, 2021
Rabbit MQ with Docker for Microservices
Rabbit MQ message broker helps to implement event-driven architecture for microservices. Instead of tight coupling multiple services, we can send and subscribe to events. In this video, I explain how to dockerize Rabbit MQ and provide a simple, but complete example of communication through Rabbit MQ.
Labels:
Docker,
Microservices,
Python,
RabbitMQ
Saturday, February 20, 2021
React and TensorFlow.js
I explain how to create React app with Yarn and how to integrate TensorFlow.js into that app. A simple model is trained with TensorFlow.js to give you a good starting point. I also show how to run the predict function and read the output.
Labels:
JavaScript,
Machine Learning,
React,
TensorFlow
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